Hadoop Architect

Primary Skill: Data Engineering, Platform Engineering or architecture roles. Deep Expertise in Pyspark.

Experience: 10+ yrs

Roles & Responsibilities

Bachelor s or master s degree in computer science or related field.

• Required Hard and Soft Skills / Experience
• Deep Expertise in PySpark, including performance tuning and optimization
• Strong python development experience in large-scale distributed environment
• Solid knowledge of Hadoop ecosystem (HDFS,Hive/Impala, YARN)
• Proven experience designing and governing enterprise, regulatory facing data platforms.
• Expertise in designing data lakes, ELT/ETL pipelines, batch and real time data processing solution
• Proficiency in programming languages such as Java, Scala and SQL
• Strong understanding of non-functional requirements and production support models
• Clear written and verbal communication skills with ability to influence across organizations

• Preferred Skills / Experience
• Financial services experience, particularly in Market Surveillance, AML, Fraud, Or Risk Technology
• Experience supporting regulatory or audit facing platforms
• Kafka and Spark Structured streaming exposure
• Familiarity with Orchestration tools(Airflow,Control-M,Oozie)
• Knowledge of data governance, lineage, and data quality controls

• Daily Responsibilities/Priorities
• Enterprise & Surveillance Architecture
• Define target state architecture and strategic roadmap for surveillance data processing platforms leveraging Hadoop,Spark, Pyspark and Python
• Establish standard architectural patterns for alert generation, enrichment, aggregation and reporting pipelines.
• Ensure architecture aligns with enterprise technology standards and Surveillance control expectation

• Solution Design and Delivery Support
• Translate surveillance business requirements(e.g, market misconduct detection, regulatory coverage) into scalable technical designs
• Review and approve detailed technical designs, ensuring alignment with functional intent, regulatory requirements, and architectural standards.
• Provide hands-on architectural guidance to engineering teams during development, testing and implementation
• Design and standardization of Spark/Pyspark frameworks supporting surveillance alert generation and enrichment
• Modernization and Optimization of large-scale Hadoop surveillance workloads to improve performance, stability and control coverage
• Implementation of enterprise-consistent architecture patterns enabling audit readiness, lineage, and regulatory traceability
• Support end-to-end delivery across the SDLC, minimizing rework and technical debt

• Architecture Governance & Leadership
• Participate in and lead architecture review forums and design walkthroughs
• Mentor senior engineers and promote adoption of Standard framework and best practices
• Influence enterprise surveillance platform strategy through architecture governance

• Documentation & Communication
• Maintain high-quality documentation, including business requirement, data definitions and process flows
• Proactively communicate risks, dependencies and potential timeline impact to stakeholders
• Non-Functional requirement and product Readiness